Department of Biomedical Engineering, Columbia University, New York, New York 10027, USA.
J Biomed Opt. 2013 Jul;18(7):076001. doi: 10.1117/1.JBO.18.7.076001.
This is the first part of a two-part paper on the application of computer-aided diagnosis to diffuse optical tomography (DOT). An approach for extracting heuristic features from DOT images and a method for using these features to diagnose rheumatoid arthritis (RA) are presented. Feature extraction is the focus of Part 1, while the utility of five classification algorithms is evaluated in Part 2. The framework is validated on a set of 219 DOT images of proximal interphalangeal (PIP) joints. Overall, 594 features are extracted from the absorption and scattering images of each joint. Three major findings are deduced. First, DOT images of subjects with RA are statistically different (p<0.05) from images of subjects without RA for over 90% of the features investigated. Second, DOT images of subjects with RA that do not have detectable effusion, erosion, or synovitis (as determined by MRI and ultrasound) are statistically indistinguishable from DOT images of subjects with RA that do exhibit effusion, erosion, or synovitis. Thus, this subset of subjects may be diagnosed with RA from DOT images while they would go undetected by reviews of MRI or ultrasound images. Third, scattering coefficient images yield better one-dimensional classifiers. A total of three features yield a Youden index greater than 0.8. These findings suggest that DOT may be capable of distinguishing between PIP joints that are healthy and those affected by RA with or without effusion, erosion, or synovitis.
这是关于计算机辅助诊断在漫射光学断层扫描（DOT）中的应用的两部分论文的第一部分。介绍了一种从 DOT 图像中提取启发式特征的方法，以及一种使用这些特征来诊断类风湿关节炎（RA）的方法。特征提取是第 1 部分的重点，而第 2 部分评估了五种分类算法的效用。该框架在一组 219 个近端指间关节（PIP）的 DOT 图像上进行了验证。总体而言，从每个关节的吸收和散射图像中提取了 594 个特征。得出了三个主要发现。首先，RA 患者的 DOT 图像在超过 90％的研究特征方面与无 RA 患者的图像存在统计学差异（p<0.05）。其次，没有检测到积液、侵蚀或滑膜炎（通过 MRI 和超声确定）的 RA 患者的 DOT 图像与确实存在积液、侵蚀或滑膜炎的 RA 患者的 DOT 图像在统计学上无法区分。因此，这组患者可能可以通过 DOT 图像诊断为 RA，而通过 MRI 或超声图像检查则无法发现。第三，散射系数图像产生更好的一维分类器。共有三个特征的约登指数大于 0.8。这些发现表明，DOT 可能能够区分健康的 PIP 关节和受 RA 影响的关节，无论是否有积液、侵蚀或滑膜炎。
